Package unifeat.featureSelection.embedded.SVMBasedMethods

Class OVA_SVM_RFE

java.lang.Object

unifeat.featureSelection.FeatureSelection

unifeat.featureSelection.embedded.EmbeddedApproach

unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods

unifeat.featureSelection.embedded.SVMBasedMethods.OVA_SVM_RFE

public class OVA_SVM_RFE
extends SVMBasedMethods

This java class is used to implement OVA_SVM_RFE method for multiclass classification based on SVM_RFE method (support vector machine method based on recursive feature elimination) in which One-Versus-All (OVA) strategy is applied to construct binary classifiers.

Author:

Sina Tabakhi

See Also:

• SVMBasedMethods
• EmbeddedApproach
• FeatureSelection

Field Summary

Fields

Modifier and Type	Field	Description
private final double	ERROR_DENOMINATOR
private final double	ERROR_TWO_CLASS_PROBLEM

Fields inherited from class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods

classLabelInTrainSet, kernelType, parameterC, TEMP_PATH

Fields inherited from class unifeat.featureSelection.embedded.EmbeddedApproach

classLabel, nameFeatures, PROJECT_PATH

Fields inherited from class unifeat.featureSelection.FeatureSelection

numClass, numFeatures, numSelectedFeature, selectedFeatureSubset, trainSet

Constructor Summary

Constructors

Constructor	Description
OVA_SVM_RFE(Object... arguments)	Initializes the parameters
OVA_SVM_RFE(String path, SVMKernelType kernelType, double c)	Initializes the parameters

Method Summary

Modifier and Type	Method	Description
void	evaluateFeatures()	Starts the feature selection process by support vector machine method based on recursive feature elimination using One-Versus-All strategy (OVA_SVM_RFE)
private double[]	getFeaturesWeights(int[] selectedFeature)	Generates binary classifiers (SVM by applying One-Versus-All (OVA) strategy) using input data and based on selected feature subset, and finally returns the weights of features

Methods inherited from class unifeat.featureSelection.embedded.SVMBasedMethods.SVMBasedMethods

buildSVM_OneAgainstOne, buildSVM_OneAgainstRest, createClassLabel

Methods inherited from class unifeat.featureSelection.embedded.EmbeddedApproach

loadDataSet, loadDataSet, newMethod, originalFeatureSet

Methods inherited from class unifeat.featureSelection.FeatureSelection

getSelectedFeatureSubset, setNumSelectedFeature, validate

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

ERROR_DENOMINATOR

private final double ERROR_DENOMINATOR

See Also:

• Constant Field Values

ERROR_TWO_CLASS_PROBLEM

private final double ERROR_TWO_CLASS_PROBLEM

See Also:

• Constant Field Values

Constructor Details

OVA_SVM_RFE

public OVA_SVM_RFE(Object... arguments)

Initializes the parameters

Parameters:

arguments - array of parameters contains (path, kernelType, Parameter c) in which path is the path of the project, kernelType is the type of kernel to use, and Parameter c is the complexity parameter C

OVA_SVM_RFE

public OVA_SVM_RFE(String path,
 SVMKernelType kernelType,
 double c)

Initializes the parameters

Parameters:

path - the path of the project

kernelType - the type of kernel to use

c - the complexity parameter C

Method Details

getFeaturesWeights

private double[] getFeaturesWeights(int[] selectedFeature)

Generates binary classifiers (SVM by applying One-Versus-All (OVA) strategy) using input data and based on selected feature subset, and finally returns the weights of features

Parameters:

selectedFeature - an array of indices of the selected feature subset

Returns:

an array of the weights of features

evaluateFeatures

public void evaluateFeatures()

Starts the feature selection process by support vector machine method based on recursive feature elimination using One-Versus-All strategy (OVA_SVM_RFE)

Specified by:

evaluateFeatures in class FeatureSelection